Operations | Monitoring | ITSM | DevOps | Cloud

Elastic's Guide to Data Visualization in Kibana

Practitioners the field of data visualizations often talk about 2 types of visualizations: exploratory vs explanatory. To quote Google definitions, “Exploratory data visualizations (EDVs) are the type of visualizations you assemble when you do not have a clue about what information lies within your data. Nov 19, 2018” Explanatory visualization, by contrast, is defined as “what happens when you have something specific you want to show an audience” (Storytelling with data blog, April 2014)

How to implement Prometheus long-term storage using Elasticsearch

Prometheus plays a significant role in the observability area. An increasing number of applications use Prometheus exporters to expose performance and monitoring data, which is later scraped by a Prometheus server. However, when it comes to storage, Prometheus faces some limitations in its scalability and durability since its local storage is limited by single nodes.

Building a Search Engine with Elastic App Search

Building a web application to solve a business problem is easy in today's world. But, how about creating an experience that lets your user spend more time on the service. To do that essentially, we need to equip the application with quintessential features like search. Most of the websites like eCommerce, Food Delivery, Social media rely on search. Search is omnipresent and one can't ignore the users searching for something on your website.

Elastic Stack Alerting Overview

Introducing the new alerting framework for the Elastic Stack bringing alert functionality directly into SIEM, APM, Uptime, and Metrics. The new alerting framework is built from the ground up and designed to offer data-driven triggers that let you do everything from send an email, to automatic Slack notifications, to even integrate with platforms like PagerDuty to initiate escalations.

Elastic Stack 7.7.0 released

We are pleased to announce the general availability of version 7.7 of the Elastic Stack. Like most Elastic Stack releases, 7.7 packs quite a punch. But more than the new features, we’re most proud of the team that delivered it. A feature-packed release like this is special during normal times. But it’s extra special today given the uncertain times we are in right now.

How to enrich logs and metrics using an Elasticsearch ingest node

When ingesting data into Elasticsearch, it is often beneficial to enrich documents with additional information that can later be used for searching or viewing the data. Enrichment is the process of merging data from an authoritative source into documents as they are ingested into Elasticsearch. For example, enrichment can be done with the GeoIP Processor which processes documents that contain IP addresses and adds information about the geographical location associated with each IP address.

Elastic at home for students and educators: A resource guide

George Lucas once said, “Education is the single most important job of the human race.” When considering the requirement of education in the mastering of any role or skill, there is no debate to the truth behind his words. Education is the cornerstone on which the future is built, which is why Elastic is launching the Elastic for Students and Educators program.

APM - Diving in to the async profiler feature of the java APM agent

Distributed tracing is great — it helps you identify (micro)services within complex architectures having issues interfering with user experience, such as high latency or errors. But once a problematic service is identified, it can be difficult to find out which methods are to blame for the slowdown. In this presentation, Felix Barnsteiner (one of the core developers of the APM Java Agent) will show you the different ways to get method-level insight into your application. Specifically, we’ll have a look at the newly added support for profiler-inferred spans that is based on a sampling profiler.